Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
o1-pro is clearly ahead on the aggregate, 45 to 35. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1-pro's sharpest advantage is in reasoning, where it averages 56.2 against 38.6. The single biggest benchmark swing on the page is MRCRv2, 59 to 38. Mixtral 8x22B Instruct v0.1 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Mixtral 8x22B Instruct v0.1. That is roughly Infinityx on output cost alone. o1-pro is the reasoning model in the pair, while Mixtral 8x22B Instruct v0.1 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. o1-pro gives you the larger context window at 200K, compared with 64K for Mixtral 8x22B Instruct v0.1.
Pick o1-pro if you want the stronger benchmark profile. Mixtral 8x22B Instruct v0.1 only becomes the better choice if coding is the priority or you want the cheaper token bill.
o1-pro
39.7
Mixtral 8x22B Instruct v0.1
31.8
o1-pro
23
Mixtral 8x22B Instruct v0.1
40
o1-pro
48.5
Mixtral 8x22B Instruct v0.1
35.5
o1-pro
56.2
Mixtral 8x22B Instruct v0.1
38.6
o1-pro
69.9
Mixtral 8x22B Instruct v0.1
53
Benchmark data for this category is coming soon.
o1-pro
52
Mixtral 8x22B Instruct v0.1
42
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
o1-pro is ahead overall, 45 to 35. The biggest single separator in this matchup is MRCRv2, where the scores are 59 and 38.
o1-pro has the edge for knowledge tasks in this comparison, averaging 69.9 versus 53. Inside this category, FrontierScience is the benchmark that creates the most daylight between them.
Mixtral 8x22B Instruct v0.1 has the edge for coding in this comparison, averaging 40 versus 23. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
o1-pro has the edge for reasoning in this comparison, averaging 56.2 versus 38.6. Inside this category, MRCRv2 is the benchmark that creates the most daylight between them.
o1-pro has the edge for agentic tasks in this comparison, averaging 39.7 versus 31.8. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
o1-pro has the edge for multimodal and grounded tasks in this comparison, averaging 48.5 versus 35.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
o1-pro has the edge for multilingual tasks in this comparison, averaging 52 versus 42. Inside this category, MMLU-ProX is the benchmark that creates the most daylight between them.
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